I would like to calculate my savings of my solar power roof system.
So i have a select of my values:
SELECT (sum("Verbrauch")/60 - sum("Bezug")/60) * $Strompreis_Maingau /1000 FROM "Meter" WHERE $timeFilter GROUP BY time(1d) fill(null)
i multiply the values with the varible "Strompreis_Maingau" where the costs/kwh is configured.
So i changed my power company and i have now an other price for one kwh.
I would like to display the daily values up to 15.12.2021 with the "old" variable and from 16.12.2021 on with a new one.
When i change the select to:
SELECT (sum("Verbrauch")/60 - sum("Bezug")/60) * $Strompreis_Maingau /1000 FROM "Meter" WHERE time < '2021-12-16' GROUP BY time(1d) fill(null)
Then i see the values only up to this date..but i would like to combine it with an addidtional select with the new variable and up from 16.12.2021.
Is this possible in some way?
Thank you!
I have the same problem, the only way to calculate with the right costs is to put the costs/kwh into the database. Everytime they change you put another datapoint to the right time and the other values and the sum are correctly calculated. You can if you want display a graph with the currency of your electricity price.
Related
sometimes it appears that one have to calculate SUM of unique TAG values in InfluxDB. How to do it?
For example I have multiple users who downloads software. Now I want to extract how many unique users downloaded it.
Following query was tested in Grafana to calculate unique users and also consider time filter applied to the database.
To do this we need to apply subquery first to calculate mean values, this basically will result a table with value 1 associated for each user:
SELECT mean("count") FROM "autogen"."downloads" WHERE $timeFilter GROUP BY "username"
Here count is an integer value that is equal to 1 for each time user downloads the software.
After we can calculate sum of these mean values, yes, this is not cheap if you have a huge database, but still is a working solution:
SELECT SUM(mean) FROM (
SELECT mean("count") FROM "autogen"."downloads" WHERE $timeFilter GROUP BY "username"
)
Please go ahead and propose best performing/more native solution, this will be nice to apply for larger DBs
Hy everyone. This is my first post on Stack Overflow so sorry if it is clumpsy in any way.
I work in Python and make postgresSQL requests to a google BigQuery database. The data structure looks like this :
sample of data
where time is represented in nanoseconds, and is not regularly spaced (it is captured real-time).
What I want to do is to select, say, the mean price over a minute, for each minute in a time range that i would like to give as a parameter.
This time range is currently a list of timestamps that I build externally, and I make sure they are separated by one minute each :
[1606170420000000000, 1606170360000000000, 1606170300000000000, 1606170240000000000, 1606170180000000000, ...]
My question is : how can I extract this list of mean prices given that list of time intervals ?
Ideally I'd expect something like
SELECT AVG(price) OVER( PARTITION BY (time BETWEEN time_intervals[i] AND time_intervals[i+1] for i in range(len(time_intervals))) )
FROM table_name
but I know that doesn't make sense...
My temporary solution is to aggregate many SELECT ... UNION DISTINCT clauses, one for each minute interval. But as you can imagine, this is not very efficient... (I need up to 60*24 = 1440 samples)
Now there very well may already be an answer to that question, but since I'm not even sure about how to formulate it, I found nothing yet. Every link and/or tip would be of great help.
Many thanks in advance.
First of all, your sample data appears to be at millisecond resolution, and you are looking for averages at minute (sixty-second) resolution.
Please try this:
select div(time, 60000000000) as minute,
pair,
avg(price) as avg_price
from your_table
group by div(time, 60000000000) as minute, pair
If you want to control the intervals as you said in your comment, then please try something like this (I do not have access to BigQuery):
with time_ivals as (
select tick,
lead(tick) over (order by tick) as next_tick
from unnest(
[1606170420000000000, 1606170360000000000,
1606170300000000000, 1606170240000000000,
1606170180000000000, ...]) as tick
)
select t.tick, y.pair, avg(y.price) as avg_price
from time_ivals t
join your_table y
on y.time >= t.tick
and y.time < t.next_tick
group by t.tick, y.pair;
I want to find the number of customers per subscription plan at the end of the acquisition month.
As you can see in the workbook, customers can change their subscription plan on any date, but I only want to find the subscription plan at the end of the acquisition month.
I created a field, called EOM Acquisition, but need to find the desired output below for any given month of acquisition. (in sample dataset only October).
How can I do that? Thanks in advance!
Please proceed like this. Create a new calculated field say calculation1 as follows-
IF [Date] = [EOM Acquisition] then [Subscription Plan] END
drag this field instead of subs plan in view and filter out null values, you'll get what you want
Another way add a calc field as follows
IF [Date] = [EOM Acquisition] then 1 ELSE 0 END
And thereafter add sum on this field as measure alongwith EOM and subscription fields.
i have this tableau workbook
basically this calculated day different between each user_id and each transaction for each user_id with this calculation
DATEDIFF('day',LOOKUP(MIN([Created At]),-1), MIN([Created At]))
that pull filters its so filter the conditions of users (We can ignore this)
and date_rante filters its for calculated day different between date range on parameter
with this calculated
lookup(min(([Created At])),0) >= [START_DATE] and
lookup(min(([Created At])),0) <= [END_DATE]
so from the frequency i want to find out the Max of different day, with this calculated
MAX({FIXED [User Id]:DATEDIFF('day',LOOKUP(MIN([Created At]),-1), MIN([Created At]))})
but it says
level of detail expressions cannot contain table calculations or the attr function
so i used this solution https://kb.tableau.com/articles/howto/finding-the-dimension-member-with-the-highest-measure-value
and from that solution, i applied with my codes into like this
MAX({FIXED [User Id]:DATEDIFF('day',INT(LOOKUP(MIN([Created At]),-1)), INT(MIN([Created At])))})
but it turns to error datediff being called with string,integer,integer
based on #Anil solution, i tried to create it, and idk why the results was like this
new picture
Presently, as far as my knowledge of tableau is, tableau doesn't allow to calculate LOD calcs or further aggregations on table calcs. To find the transactions where the user took most/max time (in days) in subsequent order- You can do this workaround..
Let's assume your datediff calc field is named as CF1. create another calc field lets say CF2 with following calculation
rank_unique([CF1])
EDIT:
Change table calcs on this field similar to CF1. putting a filter on this field will give you the dates with max(time diff) as shown in screenshot.
table calculation options on first (datediff field)
table calculation options on second field (rank_unique)
I have added third field on colors
(Please note no field used in filters just to highlight)
I am using InfluxDB and grafana. I have a data for 20 users.
Here is the query I use to display a single user:
SELECT delta FROM "measures" WHERE user_id='23545296664228'
What I want is a panel in Grafana when I can display all 20 series ?
Ideally, it would be great to be able to display/hide series to focus on a specific one.
The goal, here, is to see if there is a specific user that behaves differently from others, and be able to visually identify him
Is it possible ?
Assuming user_id is tag in measures measurement you need to use group by in query like in this example:
SELECT delta FROM "measures" WHERE time > now() - 1d GROUP BY time(1h),user_id